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SUMMARY:Generative Models for Molecular Discovery
DTSTART:20240402T151500
DTEND:20240402T161500
DTSTAMP:20260501T113727Z
UID:210dc650698ddd950c7df8199ec0e488dda0df9869512006aac73166
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr. Bilodeau is currently an assistant professor in Chemical E
 ngineering at the University of Virginia. She received her B.S. and M.S. f
 rom Northwestern University and her Ph.D. from Rensselaer Polytechnic Inst
 itute\, both in Chemical and Biological Engineering. During her Ph.D.\, sh
 e received the Lawrence Livermore Advanced Simulations and Computation Gra
 duate Fellowship\, through which she carried out research at Lawrence Live
 rmore National Laboratory. She completed a postdoc at MIT working with Kla
 vs Jensen and Regina Barzilay. Her research explores the intersection betw
 een artificial intelligence and molecular simulations with the goal of des
 igning new molecules and materials.\nMolecular discovery is key to solving
  many problems in chemistry\, ranging from identifying cures for infectiou
 s diseases to developing technologies that address climate change. While t
 here exists a large number of theoretically synthesizable molecules\, the 
 time and resource costs of experimentally characterizing those molecules m
 ake it intractable to fully explore chemical space. In recent years\, gene
 rative models have garnered excitement for their ability to rapidly discov
 er new molecules and materials. In this seminar\, we will explore 1) how g
 enerative models can be used to discover novel molecules that are optimize
 d with respect to multiple objectives or constraints and 2) how generative
  models and automated labs can be combined for autonomous molecular discov
 ery.
LOCATION:https://epfl.zoom.us/j/68447908297?pwd=OU5JUGJUSUhZc0ZNYjQ2WENvYl
 NRdz09
STATUS:CONFIRMED
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